Recognition and classification of facial expression using artificial intelligence as a key of early detection in neurological disorders

Abstract The recognition and classification of facial expressions using artificial intelligence (AI) presents a promising avenue for early detection and monitoring of neurodegenerative disorders. This narrative review critically examines the current state of AI-driven facial expression analysis in the context of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s. We discuss the potential of AI techniques, including deep learning and computer vision, to accurately interpret and categorize subtle changes in facial expressions associated with these pathological conditions. Furthermore, we explore the role of facial expression recognition as a noninvasive, cost-effective tool for screening, disease progression tracking, and personalized intervention in neurodegenerative disorders. The review also addresses the challenges, ethical considerations, and future prospects of integrating AI-based facial expression analysis into clinical practice for early intervention and improved quality of life for individuals at risk of or affected by neurodegenerative diseases.